a  d% @sddlmZmZddlZddlmZddlmZeeeeefdddZdeeeeed d d Z deeeeed d d Z dS))OptionalTupleN)Tensor)_check_same_shape)predstargetreturncCs"t|||}|}||fS)zUpdate and returns variables required to compute Cosine Similarity. Checks for same shape of input tensors. Args: preds: Predicted tensor target: Ground truth tensor )rfloat)rrr }/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torchmetrics/functional/regression/cosine_similarity.py_cosine_similarity_updates r sum)rr reductionrcCsZ||jdd}|jdd}|jdd}|||}tjtjddddd}|||S)a&Compute Cosine Similarity. Args: preds: Predicted tensor target: Ground truth tensor reduction: The method of reducing along the batch dimension using sum, mean or taking the individual scores Example: >>> target = torch.tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) >>> preds = torch.tensor([[1, 2, 3, 4], [-1, -2, -3, -4]]) >>> preds, target = _cosine_similarity_update(preds, target) >>> _cosine_similarity_compute(preds, target, 'none') tensor([ 1.0000, -1.0000]) )ZdimcSs|SNr xr r r @z,_cosine_similarity_compute..cSs|Srr rr r r rAr)r meannoneN)r Znormtorchr)rrrZ dot_productZ preds_normZ target_normZ similarityZreduction_mappingr r r _cosine_similarity_compute(s   rcCst||\}}t|||S)aCompute the `Cosine Similarity`_. .. math:: cos_{sim}(x,y) = \frac{x \cdot y}{||x|| \cdot ||y||} = \frac{\sum_{i=1}^n x_i y_i}{\sqrt{\sum_{i=1}^n x_i^2}\sqrt{\sum_{i=1}^n y_i^2}} where :math:`y` is a tensor of target values, and :math:`x` is a tensor of predictions. Args: preds: Predicted tensor with shape ``(N,d)`` target: Ground truth tensor with shape ``(N,d)`` reduction: The method of reducing along the batch dimension using sum, mean or taking the individual scores Example: >>> from torchmetrics.functional.regression import cosine_similarity >>> target = torch.tensor([[1, 2, 3, 4], ... [1, 2, 3, 4]]) >>> preds = torch.tensor([[1, 2, 3, 4], ... [-1, -2, -3, -4]]) >>> cosine_similarity(preds, target, 'none') tensor([ 1.0000, -1.0000]) )r r)rrrr r r cosine_similarityFsr)r )r ) typingrrrrZtorchmetrics.utilities.checksrr strrrr r r r s